Sharon Li

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Yiyou SunUniversity of California, BerkeleyDirección de correo verificada de berkeley.edu
John HopcroftCornell UniversityDirección de correo verificada de cs.cornell.edu
Sean Xuefeng DuPhD student, University of Wisconsin, MadisonDirección de correo verificada de wisc.edu
Ziwei LiuAssistant Professor, Nanyang Technological UniversityDirección de correo verificada de ntu.edu.sg
Jingkang YangPhD Candidate, MMLab@NTUDirección de correo verificada de ntu.edu.sg
Gao Huang （黄高）Associate Professor, Tsinghua UniversityDirección de correo verificada de tsinghua.edu.cn
Kilian WeinbergerCornell UniversityDirección de correo verificada de cornell.edu
Kaiyang ZhouAssistant Professor, Hong Kong Baptist UniversityDirección de correo verificada de hkbu.edu.hk
Xiaojin ZhuProfessor in Computer Science at University of Wisconsin-MadisonDirección de correo verificada de cs.wisc.edu
Geoff PleissAssistant Professor, University of British ColumbiaDirección de correo verificada de stat.ubc.ca
Chuan GuoResearch Scientist, FAIR, MetaDirección de correo verificada de fb.com
Jeff CluneProfessor, Comp. Sci.,U British Columbia; CIFAR AI Chair, Vector; Senior Research Advisor, DeepMindDirección de correo verificada de ubc.ca
Jason YosinskiWindscape AI; ML CollectiveDirección de correo verificada de windscape.ai
Robert D NowakKeith and Jane Morgan Nosbusch Professor in ECE, Grace Wahba Professor of Data ScienceDirección de correo verificada de wisc.edu
Leitian TaoUniversity of Wisconsin–MadisonDirección de correo verificada de cs.wisc.edu
Christopher RéComputer Science, Stanford UniversityDirección de correo verificada de cs.stanford.edu
Zhen FangAAII,University of Technology SydneyDirección de correo verificada de uts.edu.au
Hyeong Kyu ChoiUniversity of Wisconsin-Madison, Korea UniversityDirección de correo verificada de wisc.edu
Shawn ImUniversity of Wisconsin-MadisonDirección de correo verificada de wisc.edu

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Sharon Li

Otros nombresYixuan Li

University of Wisconsin-Madison

Dirección de correo verificada de cs.wisc.edu - Página principal

machine learning Reliable AI


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Stacked Generative Adversarial Networks X Huang, Y Li, O Poursaeed, J Hopcroft, S Belongie IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017	4358*	2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks S Liang, Y Li, R Srikant International Conference on Learning Representation (ICLR'18), 2018	2461	2018
Exploring the limits of weakly supervised pretraining D Mahajan, R Girshick, V Ramanathan, K He, M Paluri, Y Li, A Bharambe, ... Proceedings of the European conference on computer vision (ECCV), 181-196, 2018	1697	2018
Energy-based Out-of-distribution Detection W Liu, X Wang, J Owens, Y Li Advances in Neural Information Processing Systems 33, 2020	1459	2020
Snapshot Ensembles: Train 1, Get M for Free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger International Conference on Learning Representation (ICLR 2017), 2017	1175	2017
Generalized out-of-distribution detection: A survey J Yang, K Zhou, Y Li, Z Liu International Journal of Computer Vision 132 (12), 5635-5662, 2024	985	2024
Out-of-Distribution Detection with Deep Nearest Neighbors Y Sun, Y Ming, X Zhu, Y Li In Proceedings of International Conference on Machine Learning (ICML), 2022	529	2022
ReAct: Out-of-distribution Detection With Rectified Activations Y Sun, C Guo, Y Li Advances in Neural Information Processing Systems 34, 144-157, 2021	494	2021
Convergent Learning: Do different neural networks learn the same representations? Y Li, J Yosinski, J Clune, H Lipson, J Hopcroft International Conference on Learning Representation (ICLR), 2016	390	2016
On the Importance of Gradients for Detecting Distributional Shifts in the Wild R Huang, A Geng, Y Li Advances in Neural Information Processing Systems (NeurIPS), 2021	365	2021
VOS: Learning What You Don't Know by Virtual Outlier Synthesis X Du, Z Wang, M Cai, Y Li Proceedings of the International Conference on Learning Representations 1 (4), 8, 2022	341	2022
Mitigating Neural Network Overconfidence with Logit Normalization H Wei, R Xie, H Cheng, L Feng, B An, Y Li In Proceedings of International Conference on Machine Learning (ICML), 2022	301	2022
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space R Huang, Y Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	265	2021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges M Salehi, H Mirzaei, D Hendrycks, Y Li, MH Rohban, M Sabokrou Transactions on Machine Learning Research (TMLR), 2022	246	2022
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection J Yang, P Wang, D Zou, Z Zhou, K Ding, W Peng, H Wang, G Chen, B Li, ... NeurIPS Datasets and Benchmarks Track, 2022	240	2022
DICE: Leveraging Sparsification for Out-of-Distribution Detection Y Sun, Y Li In Proceedings of European Conference on Computer Vision (ECCV), 691-708, 2022	193	2022
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining J Chen, Y Li, X Wu, Y Liang, S Jha Proceedings of European Conference on Machine Learning and Principles and …, 2021	165	2021
PiCO: Contrastive Label Disambiguation for Partial Label Learning H Wang, R Xiao, S Li, L Feng, G Niu, G Chen, J Zhao International Conference on Learning Representations (ICLR), 2022	164	2022
Delving into Out-of-Distribution Detection with Vision-Language Representations Y Ming, Z Cai, J Gu, Y Sun, W Li, Y Li Advances in Neural Information Processing Systems (NeurIPS), 2022	162	2022
Uncovering the small community structure in large networks: A local spectral approach Y Li, K He, D Bindel, JE Hopcroft Proceedings of the 24th international conference on world wide web, 658-668, 2015	161	2015

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